ASSESSING THE IMPACT OF INCORRECT OBSERVATIONAL COVARIANCE MATRIX OVER RETRIEVAL: METHODS AND APPLICATION TO IASI DATA

The paper addresses the effect of an incorrect specified observational covariance matrix on the retrieval of atmospheric parameters from high spectral resolution infrared radiances. The case of a non-diagonal covariance matrix approximated with its diagonal is dealt with. The problem is of interest to IASI (Infrared Atmospheric Sounding Interferometer) which, because of apodization, is characterized by a non-diagonal covariance matrix. However, the diagonal alone rather than the full matrix is normally used in data assimilation and retrieval schemes because of numerical and computational efficiency. The problem will be analysed in its formal, mathematical aspects through the help of the linear approximation. In addition, a series of retrieval exercises will help to draw more general conclusions. We have found that the incorrect use of the diagonal instead of the full covariance matrix can affect the spatial vertical resolution of the retrieval and can lead to instability in the final solution, especially in the lower troposphere

KALMAN FILTER RETRIEVAL OF SEA SKIN TEMPERATURE FROM SEVIRI: A COMPARISON CASE STUDY

The high temporal resolution of data acquisition by geostationary satellites and their capability to resolve the diurnal cycle allow for the retrieval of a valuable source of information about geophysical parameters. To exploit this information we have developed a Kalman filter methodology for the retrieval of surface emissivity and temperature from radiance measurements made from geostationary platforms. The application of the retrieval methodology to SEVIRI (Spinning Enhanced Visible and Infrared Imager) infrared channels shows that we can simultaneously retrieve surface emissivity and temperature with an accuracy of ± 0.005 and ± 0.2 K, respectively. This performance is exemplified in this paper with a case study, which considers the retrieval of sea skin temperature for a target area of the Naples Gulf. Retrieval for temperature has been intercompared with similar products derived from AVHRR (Advanced Very High Resolution Radiometer) and MODIS (Moderate Resolution Imaging Spectroradiometer) satellite sensors

Using the full IASI spectrum for the physical retrieval of temperature, H2O, HDO, O3, minor and trace gases

IASI (Infrared Atmospheric Sounder Interferometer) is flying on the European MetOp series of weather satellites. Besides acquiring temperature and humidity data, IASI also observes the infrared emission of the main minor and trace atmospheric components with high precision. The retrieval of these gases would be highly beneficial to the efforts of scientists monitoring Earths climate. IASI retrieval capability and algorithms have been mostly driven by Numerical Weather Prediction centers, whose limited resources for data transmission and computing is hampering the full exploitation of IASI information content. The quest for real or nearly real time processing has affected the precision of the estimation of minor and trace gases, which are normally retrieved on a very coarse spatial grid. The paper presents the very first retrieval of the complete suite of IASI target parameters by exploiting all its 8461 channels. The analysis has been exemplified for sea surface and the target parameters will include sea surface temperature, temperature profile, water vapour and HDO profiles, ozone profile, total column amount of CO, CO2, CH4, N2O, SO2, HNO3, NH3, OCS and CF4. Concerning CO2, CH4 and N2O, it will be shown that their colum amount can be obtained for each single IASI IFOV (Instantaneous Field of View) with a precision better than 1-2%, which opens the possibility to analyze, e.g., the formation of regional patterns of greenhouse gases. To assess the quality of the retrieval, a case study has been set up which considers two years of IASI soundings over the Hawaii, Manua Loa validation station

Hyper fast radiative transfer for the physical retrieval of surface parameters from SEVIRI observations

This paper describes the theoretical aspects of a fast scheme for the physical retrieval of surface temperature and emissivity from SEVIRI data, their implementation and some sample results obtained. The scheme is based on a Kalman Filter approach, which effectively exploits the temporal continuity in the observations of the geostationary Meteosat Second Generation (MSG) platform, on which SEVIRI (Spinning Enhanced Visible and InfraRed Imager) operates. Such scheme embodies in its core a physical retrieval algorithm, which employs an hyper fast radiative transfer code highly customized for this retrieval task. Radiative transfer and its customizations are described in detail. Fastness, accuracy and stability of the code are fully documented for a variety of surface features, showing a peculiar application to the massive Greek forest fires in August 2007

Validation of statistical clustering on TES dataset using synthetic Martian spectra

In this work we present some results concerning the analysis of Thermal Emission Spectrometer (TES) data, looking at the methane Q-branch spectral signature at 1304 cm-1. Such analysis has been enabled by producing some synthetic spectral datasets, simulating the atmospheric and surface variability observed on Mars, excluding the high latitude regions. The use of synthetic spectra is aimed to provide a better comprehension of the influence that the atmospheric state vector and its composition have on the spectral behavior. This effort is important, because the TES data are characterized by a low resolution (10 cm-1) and a significant random and systematic noise which could, in principle, give results whose quality needs to be improved. We apply statistical clustering of the synthetic spectra to evaluate the effectiveness of detecting methane, and estimating its abundance

Grid-Based Atmospheric Retrievals for Reflected-Light Spectra of Exoplanets using PSGnest

Techniques to retrieve the atmospheric properties of exoplanets via direct observation of their reflected light have often been limited in scope due to computational constraints imposed by the forward-model calculations. We have developed a new set of techniques which significantly decreases the time required to perform a retrieval while maintaining accurate results. We constructed a grid of 1.4 million pre-computed geometric albedo spectra valued at discrete sets of parameter points. Spectra from this grid are used to produce models for a fast and efficient nested sampling routine called PSGnest. Beyond the upfront time to construct a spectral grid, the amount of time to complete a full retrieval using PSGnest is on the order of seconds to minutes using a personal computer. An extensive evaluation of the error induced from interpolating intermediate spectra from the grid indicates that this bias is insignificant compared to other retrieval error sources, with an average coefficient of determination between interpolated and true spectra of 0.998. We apply these new retrieval techniques to help constrain the optimal bandpass centers for retrieving various atmospheric and bulk parameters from a LuvEx-type mission observing several planetary archetypes. We show that spectral observations made using a 20\% bandpass centered at 0.73 microns can be used alongside our new techniques to make detections of $H_2O$ and $O_2$ without the need to increase observing time beyond what is necessary for a signal-to-noise ratio of 10. The methods introduced here will enable robust studies of the capabilities of future observatories to characterize exoplanets.Comment: 32 pages, 17 figures. Accepted for publication in The Astronomical Journa

Potential improvements in global carbon flux estimates from a network of laser heterodyne radiometer measurements of column carbon dioxide

We present observing system simulation experiments (OSSEs) to evaluate the impact of a proposed network of ground-based miniaturized laser heterodyne radiometer (mini-LHR) instruments that measure atmospheric column-averaged carbon dioxide (XCO2) with a 1 ppm precision. A particular strength of this passive measurement approach is its insensitivity to clouds and aerosols due to its direct sun pointing and narrow field of view (0.2). Developed at the NASA Goddard Space Flight Center (GSFC), these portable, low-cost mini-LHR instruments were designed to operate in tandem with the sun photometers used by the AErosol RObotic NETwork (AERONET). This partnership allows us to leverage the existing framework of AERONET's global ground network of more than 500 sites as well as providing simultaneous measurements of aerosols that are known to be a major source of error in retrievals of XCO2 from passive nadir-viewing satellite observations. We show, using the global 3-D GEOS-Chem chemistry transport model, that a deployment of 50 mini-LHRs at strategic (but not optimized) AERONET sites significantly improves our knowledge of global and regional land-based CO2 fluxes. This improvement varies seasonally and ranges 58%81% over southern lands, 47%76% over tropical lands, 71%92% over northern lands, and 64%91% globally. We also show significant added value from combining mini-LHR instruments with the existing ground-based NOAA flask network. Collectively, these data result in improved a posteriori CO2 flux estimates on spatial scales of 10 km2, especially over North America and Europe, where the ground-based networks are densest. Our studies suggest that the mini-LHR network could also play a substantive role in reducing carbon flux uncertainty in Arctic and tropical systems by filling in geographical gaps in measurements left by ground-based networks and space-based observations. A realized network would also provide necessary data for the quinquennial global stock takes that form part of the Paris Agreement

Strong variability of Martian water ice clouds during dust storms revealed from ExoMars Trace Gas Orbiter/NOMAD

Observations of water ice clouds and aerosols on Mars can provide important insights into the complexity of the water cycle. Recent observations have indicated an important link between dust activity and the water cycle, as intense dust activity can significantly raise the hygropause, and subsequently increase the escape of water after dissociation in the upper atmosphere. Here present observations from NOMAD/TGO that investigate the variation of water ice clouds in the perihelion season of Mars Year 34 (April 2018‐19), their diurnal and seasonal behavior, and the vertical structure and microphysical properties of water ice and dust. These observations reveal the recurrent presence of a layer of mesospheric water ice clouds subsequent to the 2018 Global Dust Storm. We show that this layer rose from 45 to 80 km in altitude on a timescale of days from heating in the lower atmosphere due to the storm. In addition, we demonstrate that there is a strong dawn dusk asymmetry in water ice abundance, related to nighttime nucleation and subsequent daytime sublimation. Water ice particle sizes are retrieved consistently and exhibit sharp vertical gradients (from 0.1 to 4.0 μm), as well as mesospheric differences between the Global Dust Storm (<0.5 μm) and the 2019 regional dust storm (1.0 μm), which suggests differing water ice nucleation efficiencies. These results form the basis to advance our understanding of mesospheric water ice clouds on Mars, and further constrain the interactions between water ice and dust in the middle atmosphere